Autonomous driving has quickly become an area of interest for vehicle manufacturers and navigation and mapping service providers. One area of interest is the use of computer vision to enable mapping and sensing of a vehicle's environment to support autonomous or semi-autonomous operation. Advances in available computing power have enabled this mapping and sensing to approach or achieve real-time operation through the machine learning feature prediction models. For example, one application of feature prediction models for autonomous driving is localization of the vehicle with respect to known reference marks such as lane markings and/or other visible environmental features labeled by the feature prediction models. However, service providers and manufacturers face significant technical challenges to obtaining training data to create feature prediction models that are able to meet the quality requirements of use cases such as autonomous driving.